1. Field of the Invention
This invention relates to quality control and, more particularly, to quality control in a multi-process environment whereby the quality of a plurality of processes can be analyzed in the aggregate for improving the overall quality of the multi-process environment.
2. Description of the Prior Art
Broadly speaking, there are at least three steps in a typical quality control process: (i) a definition of the specification of what is wanted; (ii) the production of things or units or product to satisfy the specification; and (iii) the inspection of the things produced so as to ascertain whether or not the things satisfy the specifications.
Consider a manufacturing environment in which there are commonly a plurality of processes, also known as stages or phases, among other names, through which an article of manufacture, also known as a product, a thing, or a unit, passes. For example, with an automobile assembly line, there are a number of processes in a multi-process environment such as a first process for assembling the frame of the automobile, a second process of assemblying the body of the automobile, a third process of assemblying the engine, a fourth process of assemblying the interior, a fifth process of assemblying the optional items for the particular automobile, etc. In turn, each process typically includes one or more process parameters, which have target values and tolerances, which reflect design criteria or specifications. To obtain and maintain a reasonable degree of quality in the manufacturing process, it is desirable to monitor, for example, by sampling selected parameters of the product being manufactured at the different stages in the manufacturing process. Typically, the sampling would involve an analysis of the product at each, or at selected ones, of the N-processes that go to make up the multi-processing environment.
As the parameters of the product are sampled, it becomes desirable to have some structured methodology to interpret the data acquired during the sampling process. This desirability gave rise, some many years ago, to the use of what are commonly called quality control charts. The general form of a quality control chart depicts some measure of some process parameter on the ordinate and some other variable, usually time or order of production, on the abscissa. The parameter measure may be an estimate of some characteristic like the mean or standard deviation or some percentage measure of the things, which are sampled, to evidence, for example, whether or not the thing being produced satisfies the specifications. A control chart for each parameter of each process in a multi-process environment is typically produced and interpreted in some manner as a measure of the quality of the manufacturing process. It is typical that adjustments are considered and sometimes made to the manufacturing process in response to the interpretation of the quality measure. Unfortunately, the interpretation procedures tend to focus on the individual parameters of each stage of the manufacturing process. This typically results in a need to interpret many control charts, often literally hundreds of control charts. So while a control chart is an excellent tool for monitoring a process on a routine basis, it is often extremely difficult and time consuming for a shop supervisor or engineer or other person monitoring the manufacturing process to analyze each chart on an individual basis. Also, even though the charts of the individual process parameters may be interpreted, it is difficult, at best, to interpret the quality of the overall multi-process environment through the use of known control charts.